Penerapan Metode Average-Based Fuzzy Time Series Untuk Prediksi Konsumsi Energi Listrik Indonesia - Yulian Ekananta; Lailil Muflikhah; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
With the ever-increasing amount of demand for consumption, for now the concept of forecasting is increasingly necessary as an important input to take planning and control decisions. Referring to the prediction activity, one of the techniques contained in the activity is the fuzzy time series technique. Fuzzy time series is an algorithm used for prediction. Prediction using this fuzzy time series works to store data in the past then generate new value in the show in the future. The resulting output is the result of the prediction. The advantage of time series method is not to require assumptions compared to other prediction methods. The method of fuzzy time series process is not too complicated so it is easy to develop. There are many types of methods using fuzzy time series in its development, one of them is the average-based fuzzy time series. This method is an average-based fuzzy time series method that is able to determine the effective interval length, so as to provide predictive results with a good degree of accuracy. In its implementation, this research applies method of average-based fuzzy time series for prediction of electric energi consumption. The data of electric energi consumption is chosen because it has the right characteristic that is included in the trend data class. In the test section performed using test while using the traning data as much as the total amount of data 43 produces AFER 9.24. While using the MAPE 14,27%. These results include good criteria.